A Multicultural Nomad and Diasporic Intellectual: In Honour of Sneja Gunew
Bibliographic record
Abstract
Abstract This chapter honours the work of Professor Sneja Gunew who died in January 2024. It pays particular attention to how her analyses of Australian multiculturalism remain pertinent to the pursuit of migration studies on Indigenous lands. Gunew’s family migrated to Australia as Displaced Persons when she was four years old and migration and displacement were themes she explored across her vast generative body of work. Gunew was at the vanguard of the burgeoning and intersecting fields of multicultural literature and critical multiculturalism, to which she brought a strong grounding in feminist and postmodern theory. Of special interest in this chapter is how Gunew’s work on and in Australia was received before she moved to Canada in 1993. As will be seen, Gunew was a multicultural nomad and diasporic intellectual, but she never left Australia behind, and it remained central to her life and work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".